In a digital image generating apparatus such as a digital camera, a digital video camera, a printer, and a display, a variety of image generating technologies have been known for generating output images based on the difference between uncorrected pixels, i.e., pixels to be corrected, in an input image and smoothed pixels obtained by smoothing the uncorrected pixels.
For example, Published Japanese Translation of PCT Application No. 2000-511315 discloses an image generating method called a “center/surround retinex” (hereinafter, a “retinex method”) that models human visual characteristics by relatively compressing a dynamic range of the input image.
More particularly, the retinex method relatively compresses the dynamic range of an entire image by suppressing low frequency component read from the input image using a low-pass filter. Let I(x, y) denote each pixel value of the uncorrected pixels from the input image, which indicates brightness or luminance of each pixel and is represented by a numeric value ranging from 1 to 256 and let LPF(I(x, y)) denote each pixel value of the smoothed pixels, which is a low frequency component generated by the low-pass filter, then the retinex method outputs the output image having pixel values (O(x, y)) that are expressed as O(x, y)=log(I(x, y))−log(LPF(I(x, y))).
A more particular example is explained with reference to FIGS. 11A to 11H. FIGS. 11A to 11H are exemplary images and graphs for explaining a conventional image generating apparatus. In more detail, FIGS. 11B, 11C, 11E, 11F, and 11H are exemplary graphs having pixel values generated along a line A-B in FIG. 11A in an output image generating process on a vertical axis and pixel positions on a horizontal axis. FIG. 11D is a graph of a conventional tone table “f” having input values on the horizontal axis and output values obtained by converting the input values on the vertical axis.
As illustrated in FIGS. 11A to 11H, the conventional image generating apparatus receives an input image, for example, the image illustrated in FIG. 11A, and then retrieves position information of each pixel and each uncorrected pixel at each pixel position from the input image, for example, as illustrated in FIG. 11B. Then, the conventional image generating apparatus generates the smoothed pixels from the uncorrected pixels using the low-pass filter, for example, as illustrated in FIG. 11C. In addition, the conventional image generating apparatus uses a tone table such as the table “f” illustrated in FIG. 11D to convert tone of each uncorrected pixel to generate each tone-converted input pixel, for example, as illustrated in FIG. 11E, as well as to convert the tone of each smoothed pixel to generate each tone-converted smoothed pixel, for example, as illustrated in FIG. 11F. The tone table is a substantially logarithmic table that converts the tone of each of the uncorrected pixels and the smoothed pixels. Then, the conventional image generating apparatus uses differences between the tone-converted uncorrected pixels and the tone-converted smoothed pixels as well as the tone-converted smoothed pixels to generate the output image, for example, as illustrated in FIGS. 11G and 11H. More particularly, the conventional image generating apparatus adds each difference between pixel values of the tone-converted uncorrected pixels and pixel values of the tone-converted smoothed pixels to a median pixel value of the uncorrected pixels, which is a value of 128 in the exemplary image illustrated in FIG. 11H, to generate the output image.
However, the conventional image generating apparatus generates images of degraded quality when the uncorrected pixels have high or low pixel values.
Explaining more particularly with reference to FIGS. 11A to 11H, the uncorrected pixels having higher pixel values (for example, a highlight portion near a point A) illustrated in FIG. 11A) and lower pixel values (for example, a shadow portion near a point B) illustrated in FIG. 11A) has relatively approximate pixel values in terms of the uncorrected pixels and the smoothed pixels, for example, as illustrated in FIGS. 11B and 11C. The resulting output images have pixel values on the highlight and shadow portions that are close to the median, for example, as illustrated in FIG. 11H, resulting in degradation of the output images (for example, see the highlight and shadow portions in FIG. 11G).